A neural network versus Black-Scholes: a comparison of pricing and hedging performances
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DOI: 10.1002/for.867
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References listed on IDEAS
- Chesney, Marc & Scott, Louis, 1989. "Pricing European Currency Options: A Comparison of the Modified Black-Scholes Model and a Random Variance Model," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(3), pages 267-284, September.
- Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
- Garcia, Rene & Gencay, Ramazan, 2000.
"Pricing and hedging derivative securities with neural networks and a homogeneity hint,"
Journal of Econometrics, Elsevier, vol. 94(1-2), pages 93-115.
- René Garcia & Ramazan Gençay, 1998. "Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint," CIRANO Working Papers 98s-35, CIRANO.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Hutchinson, James M & Lo, Andrew W & Poggio, Tomaso, 1994.
"A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks,"
Journal of Finance, American Finance Association, vol. 49(3), pages 851-889, July.
- James M. Hutchinson & Andrew W. Lo & Tomaso Poggio, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks," NBER Working Papers 4718, National Bureau of Economic Research, Inc.
- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999.
"A simple variable selection technique for nonlinear models,"
SFB 373 Discussion Papers
1999,26, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.
- Scott, Louis O., 1987. "Option Pricing when the Variance Changes Randomly: Theory, Estimation, and an Application," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(4), pages 419-438, December.
- Timo Teräsvirta & Chien‐Fu Lin & Clive W. J. Granger, 1993. "Power Of The Neural Network Linearity Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(2), pages 209-220, March.
- Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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Cited by:
- Gradojevic Nikola, 2016.
"Multi-criteria classification for pricing European options,"
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- Nikola Gradojevic, 2015. "Multi-criteria Classification for Pricing European Options," Working Paper series 15-13, Rimini Centre for Economic Analysis.
- Yoshio Kajitani & A. Ian Mcleod & Keith W. Hipel, 2005. "Forecasting nonlinear time series with feed-forward neural networks: a case study of Canadian lynx data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 105-117.
- Beatriz Salvador & Cornelis W. Oosterlee & Remco van der Meer, 2020.
"Financial Option Valuation by Unsupervised Learning with Artificial Neural Networks,"
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- Beatriz Salvador & Cornelis W. Oosterlee & Remco van der Meer, 2020. "Financial option valuation by unsupervised learning with artificial neural networks," Papers 2005.12059, arXiv.org.
- Alois Weigand, 2019. "Machine learning in empirical asset pricing," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 93-104, March.
- Anindya Goswami & Sharan Rajani & Atharva Tanksale, 2020. "Data-Driven Option Pricing using Single and Multi-Asset Supervised Learning," Papers 2008.00462, arXiv.org, revised Dec 2020.
- Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
- Michael Weba, 2024. "Investment strategies based on forecasts are (almost) useless," Papers 2408.01772, arXiv.org.
- Maciej Wysocki & Robert Ślepaczuk, 2020. "Artificial Neural Networks Performance in WIG20 Index Options Pricing," Working Papers 2020-19, Faculty of Economic Sciences, University of Warsaw.
- Zhonghao Xian & Xing Yan & Cheuk Hang Leung & Qi Wu, 2024. "Risk-Neutral Generative Networks," Papers 2405.17770, arXiv.org.
- Lahmiri, Salim, 2017. "Modeling and predicting historical volatility in exchange rate markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 387-395.
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